关键词: 混合蛙跳算法, 早熟收敛, 高斯变异, 柯西变异, 优化

Abstract: Shuffled Frog Leaping Algorithm（SFLA） is a new group evolutionary algorithm prompted by the natrural biological phenomena, and it has fast calculation speed and strong search capability. But its local search ability is weak and it is easily caught in prematrue convergence. Combining with the advantages of Cauchy mutation and Gaussian mutation, a modified SFLA（MSFLA） is proposed to overcome the shortcoming. The MSFLA’s convergence speed is enhanced and the pheonomena that SFLA is trapped in local optimal solution will be avoided to a certain extent, so its ability of problem sloving for complex functions is improved. And experimental results prove the validity of the new SFLA.

Key words: Shuffled Frog Leaping Algorithm, premature convergence, Gaussian mutation, Cauchy mutation, optimization